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How distance to infectious source affects SARS-CoV-2 transmission rate in indoor areas

Resource type
Thesis type
(Thesis) M.Sc.
Date created
The importance of distance to infectious source in spreading Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is undeniable. Since the COVID-19 outbreak, there has been a growing scholarship investigating its dynamics of spread using modelling. While this literature has thoroughly studied the effect of social distancing and infectious droplets profile on infection spread, there exists a gap, where distance as an independent parameter is studied, considering the behaviour and location of individuals. Distance can be analyzed independently of transmission routes, the size of droplets, the distance that droplets can travel and the air-circulation state in the indoor areas. In this thesis the probability of getting infected for each individual was modeled as a function of their distance to source and contact time. Data from three early pandemic outbreaks were used to choose the best candidate among the suggested models. Then we found the maximum likelihood estimator (MLE) of model parameters for each of these datasets. Four methods were used for calculating the confidence and credible intervals of the MLE values, since some of these methods did not provide valid results. The credible interval result of two out of three datasets show that increasing distance to the infectious source, in indoor spaces with the air-circulation system turned on, reduces the probability of getting infected. These results can be useful for studying similar infectious diseases, simulating the probability of getting infected in similar environments, finding effective baseline distances that result in low infection risks and informing policy makers on how they could craft policies which could slow down/stop such infections from spreading.
44 pages.
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Copyright is held by the author(s).
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Thesis advisor: Tupper, Paul
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